Hi Susan,
Using the syntax below matchit will estimate a propensity score using all the variables
you list in the model, and then will match subjects based on their propensity scores.
If you want to match on each variable individually you could consider exact matching or
coarsened exact matching (CEM).
Liz
On Dec 9, 2015, at 9:27 AM, Susan Kamal
<susan.kamal(a)gmail.com> wrote:
Hello,
I have a question regarding nearest matching method. my function is as follows: m.out
<- matchit(treat ~ SEX + ETHN + EDUC + log_VL_BL + CD4_BL + Dur_HIV + hepC + hepB +
IVD, data = mydata, method= "nearest")
Dur_HIV is the duration og HIV infection of a patient. How is a 1:1 matching done? I do
not have 2 patients with the same duration of HIV infection in days. Does it take the
nearest duration? Also is the algorithm atching 1:1 per variable or for all the
variables?
Thanks,
Susan
--
Regards,
Susan Kamal
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